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20222026
most citedSolving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

18 citations · 36 across the 17 of their papers we have counts for

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Showing cs.IRShow all

8 papers · 1 filter

cs.IR2025

RALLRec+: Retrieval Augmented Large Language Model Recommendation with Reasoning

Sichun Luo, Jian Xu, Xiaojie Zhang +4

Large Language Models (LLMs) have been integrated into recommender systems to enhance user behavior comprehension. The Retrieval Augmented Generation (RAG) technique is further inc…

cs.IR2025

RALLRec: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning

Jian Xu, Sichun Luo, Xiangyu Chen +3

Large Language Models (LLMs) have been integrated into recommendation systems to enhance user behavior comprehension. The Retrieval Augmented Generation (RAG) technique is further…

cs.IR2024★ 5 cited

Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation

Sichun Luo, Yuxuan Yao, Bowei He +9

Conventional recommendation methods have achieved notable advancements by harnessing collaborative or sequential information from user behavior. Recently, large language models (LL…

cs.IR2023★ 5 cited

RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation

Sichun Luo, Bowei He, Haohan Zhao +9

Large Language Models (LLMs) have demonstrated remarkable capabilities and have been extensively deployed across various domains, including recommender systems. Prior research has…

cs.IR2023★ 1 cited

PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training

Sichun Luo, Yuanzhang Xiao, Xinyi Zhang +3

Federated recommendation systems employ federated learning techniques to safeguard user privacy by transmitting model parameters instead of raw user data between user devices and t…

cs.IR2022★ 1 cited

Towards Communication Efficient and Fair Federated Personalized Sequential Recommendation

Sichun Luo, Yuanzhang Xiao, Yang Liu +2

Federated recommendations leverage the federated learning (FL) techniques to make privacy-preserving recommendations. Though recent success in the federated recommender system, sev…

cs.IR2022★ 1 cited

HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations

Sichun Luo, Xinyi Zhang, Yuanzhang Xiao +1

The recent popularity of edge devices and Artificial Intelligent of Things (AIoT) has driven a new wave of contextual recommendations, such as location based Point of Interest (PoI…

cs.IR2022★ 1 cited

Personalized Federated Recommendation via Joint Representation Learning, User Clustering, and Model Adaptation

Sichun Luo, Yuanzhang Xiao, Linqi Song

Federated recommendation applies federated learning techniques in recommendation systems to help protect user privacy by exchanging models instead of raw user data between user dev…